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Rice Science, 2018, 25(6): 340−349
Cover Crops as Affecting Soil Chemical and Physical
Properties and Development of Upland Rice and Soybean
Cultivated in Rotation
Adriano Stephan NASCENTE, Luis Fernando STONE (Embrapa Arroz e Feijão (CNPAF), Rodovia GO-462, km 12 Zona Rural, CP. 179, 75375-000, Santo Antônio de Goiás, GO, Brasil)
Abstract: Cover crops can provide changes in soil chemical and physical properties, which could allow a
sustainable development of soybean and upland rice rotation in Brazilian Cerrado. The objective of this
study was to determine the effects of cover crops (cultivated in the offseason) in the soybean-upland rice
rotation (cultivated in the summer season) on the soil chemical and physical properties, yield components
and grain yield of the cash crops. The experimental design was a randomized block design in factorial
scheme 4 × 2 with six replications. Treatments were composed by four cover crops: fallow, millet
(Pennisetum glaucum) + Crotalaria ochroleuca, millet + pigeon pea (Cajanus cajans), and millet + pigeon
pea + Urochola ruziziensis in the offseason with one or two cycles of cover crops, with rice (Oryza sativa)
or soybean (Glycine max) in the summer season. Cover crops alone provided no changes in soil
chemical properties. However, the rotation cover crops / cash crops / cover crops / cash crops reduced
pH, Al and H + Al and increased Ca, Mg, K and Fe contents in the soil. The cover crops millet + pigeon
pea and millet + pigeon pea + U. ruziziensis improved soil physical properties in relation to fallow,
especially in the 0–0.10 m soil layer. In spite of the improvement of the soil physical properties after two
years of rotation with cover crops and cash crops, the soil physical quality was still below the
recommended level, showing values of macroporosity, S index and soil aeration capacity lower than 0.10
m3/m
3, 0.035 and 0.34, respectively. Upland rice production was higher under mixtures of cover crops
than under fallow, mainly because of soil physical changes done by these mixtures of cover crops.
Soybean grain yield was similar under all cover crops tested, but was higher after the rotation cover crops /
upland rice / cover crops than after only one cycle of cover crops.
Key words: crop rotation; no-tillage system; sustainable agriculture; tropical agriculture; rice; soybean
Upland rice cultivation has been increasing worldwide
because water availability for irrigation has been
decreasing, mainly because of rapid growth in industry
and urban centers. Therefore, the development of
technologies that increase upland rice yields under
aerobic conditions, thereby saving water, would be an
effective strategy to improve global rice grain
production and avoid water shortage (Nascente et al,
2013a). The use of technologies such as no-tillage
system (NTS), using cover crops and crop rotation,
may represent a viable alternative to reduce the impact
on intensive land use and could promote the
improvement of chemical and physical soil properties
(Carneiro et al, 2008; Silva et al, 2011; Pacheco et al,
2013; Nascente et al, 2014, 2015, 2016). With the use
of cover crops, which is a conservation practice, plant
species are grown and straw maintained on the soil
surface in order to ensure or increase the productive
capacity of the soil (Boer et al, 2007; Carvalho et al,
2011; Nascente et al, 2013a). Thus, when these plants
are incorporated into the production system, they will
act as soil conditioners (Moreti et al, 2007; Nascente
et al, 2015).
In the Cerrado region of Brasil, the soybean and
Received: 8 November 2017; Accepted: 23 April 2018
Corresponding author: Adriano Stephan NASCENTE ([email protected]; [email protected])
Copyright © 2018, China National Rice Research Institute. Hosting by Elsevier B V
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Peer review under responsibility of China National Rice Research Institute
http://dx.doi.org/
Adriano Stephan NASCENTE, et al. Cover Crops on Rotation Upland Rice and Soybean 341
corn succession (CONAB, 2017) prevails. However,
the continued use of the same cash crops can bring
phytosanitary problems for these crops, and therefore,
it is not a sustainable practice. The use of cover crops
and other cash crops options in succession, such as
rice, can provide significant benefits for the agriculture
in this region, such as reduction in the infestation of
insects, diseases and weeds.
NTS is consolidated as conservationist technology
among farmers in the Cerrado region (Carvalho et al,
2004; Pacheco et al, 2013). Its effectiveness is related,
among other factors, to the amount and quality of crop
residues, which has great importance for Cerrado
sustainability (Pires et al, 2008). Thus, the species of
cover crops used should have high biomass production
capacity, and straw must have impact on the soil
surface and ability to promote significant nutrient
cycling (Crusciol et al, 2005, 2015; Nascente et al,
2013a). In this case, species of cover crops would
provide benefits such as greater conservation of soil
moisture, protection against soil erosion, significant
increases in soil fertility and collaborate on integrated
management of pests, diseases and weeds (Fageria
et al, 2005). Legumes species can also influence the
water storage capacity of the soil and reduce the loss
of carbon and nitrogen in intensified systems (Drinkwater
et al, 1998). Besides, the interaction of the cover crops
with the physical attributes of the soil is related to the
intrinsic characteristics of each species, the management
of the cultural residues and the edaphoclimatic
conditions of each region (Sousa Neto et al, 2008).
Therefore, the effects of cover crops on the physical
properties of the soils should be evaluated when cover
crops are used alone and in mixture. However, there
are few studies on effects of cover crops alone and in
mixture, on soil properties in the Cerrado region.
Millet (Pennisetum glaucum) is a cover crop option,
due to high biomass production, fast straw degradation,
which releases nutrients to the soil that can be used for
the following crop (Nascente et al, 2013a, 2014, 2015).
Perennial forages such as Urochloa, for large biomass
production and greater persistence in soil, are other
options (Crusciol et al, 2015). In addition, there is
pigeon pea legume (Cajanus cajans) and sunn hemp
(Crotalaria spp.) which besides the production of
biomass, can fix atmospheric nitrogen (Torres et al,
2008). Nascente et al (2016) reported that the use of
millet as cover crop alone or intercropped with U.
ruziziensis or C. spectabilis is a management practice
option that provides high rice grain yield.
However, despite the options of cover crops species
and the benefits provided, the majority of farmers in
the Cerrado region do not use species of cover crops
in their agricultural areas, and even less in species
mixtures. Studies to identify techniques for cover
crops intercropping that promote beneficial changes in
chemical and physical attributes in the soil, which
provides increase in crop yields to be included in the
soybean / rice rotation in the Cerrado region, may
favor the expansion of the NTS in the tropical region
as well as the adoption of this technology. Therefore,
the objective of this work was to determine the effects
of the use of cover crops (cultivated in the offseason)
in the soybean / upland rice rotation (cultivated in the
summer season) on the chemical and physical properties
of the soil, and yield components and grain yield of
the cash crops.
MATERIALS AND METHODS
Site description
The experiments were conducted at Capivara Farm of
the Embrapa Rice and Beans Unit, which is located in
Santo Antônio de Goiás, GO, Brazil at 16º28'00" S
and 49º17'00" W and 823 m of elevation. The average
annual rainfall was between 1 500 and 1 700 mm, and
the average annual temperature was 22.7 ºC, ranging
annually from 14.2 ºC to 34.8 ºC. During the period of
this study, the temperature and the amount of rainfall
data were recorded (Supplemental Fig. 1).
The soil was classified as a clayey loam (kaolinitic,
thermic Typic Haplorthox) acidic soil (Embrapa, 2006).
Prior to the study in 2015, chemical and physical
analyses were performed in a depth range of 0–0.20 m
for the initial characterization of the area (Table 1).
Chemical and physical analyses were performed
according to the methodology proposed by Donagema
et al (2011). The experimental area had been cultivated
in a crop-livestock integration using a no-tillage
system for seven consecutive years, followed by a
crop rotation program of soybean (summer), rice
(summer) and irrigated common bean (winter), corn +
Urochloa (summer), and two years of grazing pasture.
Experimental design and treatments
The experimental design was a randomized block
design in factorial scheme 4 × 2 with six replications,
during two summer seasons. Treatments were composed
by four cover crops: fallow, millet (Pennisetum
342 Rice Science, Vol. 25, No. 6, 2018
glaucum) + Crotalaria ochroleuca, millet + pigeon
pea (Cajanus cajans), and millet + pigeon pea +
Urochola ruziziensis in the offseason with one or two
cycles of cover crops. In the first summer season, half
of the trial was cultivated with rice and half with
soybean in independent plots. In the second summer
season, we inverted, place that was with rice now was
cultivated with soybean and vice-versa (Table 2). The
plots had the dimension of 12 m × 14 m. The usable
area of the plot was composed of the eight 12-meter-
long central rows of rice or soybean. A corridor 2 m in
width was left between the plots.
Cover crops management
The cover crops were sown on March, 2015 and on
March, 2016 (Table 2). A seeding rate of 20, 20, 20
and 10 kg/hm2 pure live seeds was applied for millet,
C. ochroleuca, pigeon pea and U. ruziziensis,
respectively. All species were sown in 45 cm spacing.
Sowing was carried out with a seeder fertilizer at the
depth of 5 cm and without the use of fertilizers. The
cover crop plants were not irrigated. Cover crops were
desiccated with a glyphosate application (1.8 kg/hm2
acid equivalent) on 29th October, 2015 and 26th
October, 2016. Fifteen days after, cover crops were
managed with a straw crushing-shredding device
(Triton®), leaving the straw on the ground.
Soybean management
The sowing of soybean cultivar BRSGO 6959 RR was
performed mechanically on 6th November, 2015 and
11th November, 2016, using a no-till seeder (Semeato,
Personale Drill 13, Passo Fundo, Brazil) with a row
spacing of 0.45 m and a density of 18 pure live seeds
per mater. The soybean seeds were inoculated with
Bradyrhizobium japonicum. Seedling emergence
occurred at 6 and 5 d after sowing in 2015/2016 and
2016/2017, respectively. The base fertilization, to be
applied in the sowing furrows, was calculated
according to the soil chemical characteristics and the
recommendations of Sousa and Lobato (2003).
Therefore, the amount of fertilizer put at sowing time
was 90 kg/hm2 P2O5, as triple superphosphate, and 48
kg/hm2 K2O, as potassium chloride, in both years.
Cultural practices were performed according to
standard recommendations for a soybean crop to keep
the area free from weeds, diseases and insects.
Rice crop management
The sowing of rice cultivar from a mutant line
07SEQCL441 CL, which was derived from a
Primavera variety and was resistant to the Imazapyr +
Imazapic herbicide, was performed mechanically on
1st December, 2015 and 17th November, 2016 using
no-till seeder (Semeato, model Personale Drill 13,
Passo Fundo, RS, Brazil) with a row spacing of 0.35
m and a density of 80 pure live seeds per meter.
Seedling emergence occurred at 5 d after sowing in
Table 1. Chemical soil attributes in 2015.
Soil attribute Value
Layer (cm) 0–20
pH 5.4
Soil organic matter (g/kg) 27.0
K (mmol/L) 3.8
P (mg/L) 7.7
Ca (mmol/L) 32
Mg (mmol/L) 14
Al (mmol/L) 0.0
H + Al (mmol/L) 37
Cu (mg/L) 2.0
Zn (mg/L) 4.4
Fe (mg/L) 32
Mn (mg/L) 26
Cation exchange capacity (mmol/L) 86.8
Base saturation (%) 57.4
Sand (g/kg) 140
Silt (g/kg) 440
Clay (g/kg) 420
Table 2. Cover crops and cash crops cultivated during the trials.
2015 2015/2016 2016 2016/2017
Cover crop Cash crop Cover crop Cash crop
M + C Upland rice M+ C Soybean
M + P Upland rice M + P Soybean
M + P + U Upland rice M + P + U Soybean
Fallow Upland rice Fallow Soybean
M + C Soybean M + C Upland rice
M + P Soybean M + P Upland rice
M + P + U Soybean M + P + U Upland rice
Fallow Soybean Fallow Upland rice
Cover crop (CC) Biomass (t/hm2)
M + C 12.7 b
M + P 12.4 b
M + P + U 14.9 a
Fallow 8.3 c
Crop rotation (CR)
CC/cash crop (2015/2016) 9.7 b
CC/cash crop/CC/cash crop (2016/2017) 18.1 a #
ANOVA (F probability)
Cover crop (CC) < 0.001
Crop rotation (CR) < 0.001
CC × CR 0.2083
M, Millet; C, Crotalaria; P, Pigeon pea (Cajanus cajans); U,
Urochloa ruziziensis. # This value represents the sum of biomass production in
2015/2016 (9.7 t/hm2) with 2016/2017 (8.4 t/hm2).
Means followed by the same letter in columns do not differ by
the Turkey test for P < 0.05.
Adriano Stephan NASCENTE, et al. Cover Crops on Rotation Upland Rice and Soybean 343
both seasons. The base fertilization, to be applied in
the sowing furrows, was calculated according to the
soil chemical characteristics and the recommendations
of Sousa and Lobato (2003). Therefore, sowing
fertilization was 15 kg/hm2 N as urea, 90 kg/hm
2 P2O5
as triple superphosphate, and 45 kg/hm2 K2O as
potassium chloride in both years. Nitrogen topdressing
fertilization with 60 kg/hm2 N (as urea) was done 40 d
after the rice emergence. Cultural practices were
performed according to standard recommendations for
a rice crop to keep the area free from weeds, diseases
and insects.
Soil chemical measurements
Soil chemical characteristics (pH, SOM, P, H + Al, Al,
K, Ca and Mg) were determined for the 0–0.05,
0.06–0.10 and 0.11–0.20 m layers according to
Donagema et al (2011). Soil samples were taken on
March both in 2016 and 2017. Eight subsamples were
collected for each composite sample in each plot. The
soil pH was determined in a 0.01 mol/L CaCl2
suspension (1:2.5 soil/solution). Exchangeable Ca, Mg
and Al were extracted with neutral 1 mol/L KCl in a
1:10 soil/solution ratio and determined by titration
with a 0.025 mol/L NaOH solution. Phosphorus and
exchangeable K were extracted with a Mehlich 1
extracting solution (0.05 mol/L HCl in 0.0125 mol/L
H2SO4). The extracts were colorimetrically analyzed
for P, and flame photometry was used to analyze K.
Soil organic matter was determined by the method of
Walkley and Black (1934).
Soil physical measurements
Soil samples with disturbed and undisturbed structure
were collected in all treatments in June 2015 (initial
sample) and in May 2017 (final analysis), in the
0–0.10 and 0.11–0.20 m layers, with nine replicates.
The soil samples with disturbed structure were used
to determine the soil particle density (PD) by the
volumetric flask method. The undisturbed samples,
collected in cylinders 0.05 m in diameter and 0.05 m
in height, were used to determine soil water retention
curve and soil bulk density (BD). The total porosity
(TP) was calculated by the equation: TP = (1 – BD /
PD). Microporosity (Mip) was determined by the
water content retained at 6 kPa tension, and
macroporosity (Map) was obtained by the difference
between TP and Mip (Donagema et al, 2011). The soil
water retention curves were determined using the
centrifugal method (Freitas Júnior and Silva, 1984)
and they were adjusted by means of nonlinear
regression using the mathematical model proposed by
van Genuchten (1980), given by:
θ = (θsat – θres) [1 + (αh)n]
-m + θres (1)
where , sat and res are the soil water contents
corresponding to the tension h, saturation and residual
moisture, respectively; h is the matrix water tension of
the soil in kPa, n and m (m = 1 – 1 / n) are
dimensionless empirical fitting parameters and is a
parameter expressed in kPa-1
.
Based on the parameters obtained, the S index,
tangent to the soil water retention curve at the
inflection point, was determined according to the
equation (Dexter, 2004):
S = -n (θsat – θres)(1 + 1 / m)-(1 + m)
(2)
Soil air capacity (SAC) was calculated according to
the relation (Reynolds et al, 2002):
SAC = (TP – FC) / TP (3)
in which FC is the field capacity, considered equal
to the soil water content at 8 kPa.
Available water capacity (AWC) was calculated by
the difference between the FC and the water content at
1 500 kPa, considered the permanent wilting point
(PWP), multiplied by the thickness of the considered
layer.
Soybean yield measurements
Soybean was harvested on 25th February, 2016 and on
13th February, 2017 in the usable area, using a
mechanical harvester. The soybean grains were
weighed, and the yields were adjusted to a moisture
content of 13% and converted to kg/hm2. Agronomic
characteristics, including number of pods per plant
and number of seeds per pod, were evaluated for 10
randomly chosen plants per plot, along with the
100-grain weight (calculated from eight random samples
per plot, adjusted to a moisture content of 13%).
Rice yield measurements
Rice was harvested on 14th March, 2016 and on 22nd
March, 2017 in the usable area, using a mechanical
harvester. Plots were evaluated for the number of
panicles per plant, which was determined by counting
the number of panicles within 1.0 m of one of the
rows in the useful area of each plot. The number of
grains per panicle and 1000-grain weight (water content
adjusted to 13%) were randomly evaluated from each
plot. Grain yield was determined by weighing the
344 Rice Science, Vol. 25, No. 6, 2018
harvested grain of each plot.
Statistical analysis
For statistical analysis, the SAS Statistical Software,
SAS Institute, Cary, NC, USA (SAS, 1999) was used.
Data were subjected to an analysis of variance, and
when the F test proved significant, the data were
compared by a Tukey’s test. Pearson’s correlation analysis
was also performed among the physical properties.
RESULTS
The mix millet + pigeon pea + Urochloa produced the
highest biomass and differed from the others (Table 2).
Fallow produced the lowest biomass and differed from
the others. When comparing the biomass of different
cover crop rotations, two cycles of cover crops
produced more biomass and differed from the only
one cycle of cover crops (Table 2).
There was no interaction between cover crops and
growing seasons for the soil nutrients evaluated (Table
3). Cover crops and the fallow provided no significant
changes in the pH, Ca, Mg, Al, H + Al, P, K, SOM,
Cu, Fe, Mn and Zn content in the soil at layers 0–0.05
m, 0.06–0.10 m and 0.11–0.20 m (Table 3). However,
growing seasons significantly affected chemical soil
properties. At layer 0–0.05 m, pH, Ca, Mg, K and Fe
contents were higher in the soil under two cycles of
cover crops than soil under one cycle of cover crops
(Table 3). In the same layer (0–0.05 m), Al, H + Al,
Cu, Mn and Zn contents were higher under soil with
one cycle of cover crops than under soil with two
cycles of cover crops. Phosphorus and soil organic
matter (SOM) contents were similar in both years (one
or two cycles of cover crops).
In the depth of 0.06–0.10 m, pH, Ca, Mg, K and Fe
contents were higher under two cycles of cover crops
than under one cycle (Table 3). On the other hand, H +
Table 3. Soil chemical properties (0–0.05, 0.06–0.10 and 0.11–0.20 m in depth) at cash crop harvesting as affected by crop rotations (March
2016 and March 2017).
Treatment pH
Ca (mmol/L)
Mg (mmol/L)
Al (mmol/L)
0–0.05 0.06–0.10 0.11–0.20 0–0.05 0.06–0.10 0.11–0.20 0–0.05 0.06–0.10 0.11–0.20 0–0.05 0.06–0.10 0.11–0.20
CC M + C 5.37 a 5.13 a 5.08 a 28.92 a 19.70 a 20.49 a 12.93 a 8.15 a 7.58 a 0.67 a 1.25 a 1.08 a
M + P 5.34 a 5.12 a 5.12 a 28.31 a 20.32 a 18.63 a 13.86 a 7.76 a 6.75 a 0.75 a 1.25 a 1.08 a
M + P + U 5.30 a 5.13 a 5.08 a 26.92 a 18.80 a 18.16 a 12.65 a 8.21 a 7.20 a 0.92 a 1.08 a 1.08 a
Fallow 5.29 a 5.17 a 5.13 a 27.63 a 20.85 a 21.24 a 11.54 a 7.84 a 7.51 a 0.75 a 1.17 a 1.08 a
CR 2016 5.10 b 4.89 b 4.82 b 19.79 b 15.41 b 13.26 b 11.46 b 7.57 b 5.45 b 0.92 a 1.25 a 1.25 a
2017 5.54 a 5.39 a 5.38 a 36.10 a 24.42 a 26.00 a 13.53 a 8.41 a 9.08 a 0.63 b 1.13 a 0.92 b
ANOVA CC 0.9080 0.9706 0.8910 0.8427 0.6618 0.2028 0.8095 0.9441 0.7225 0.7329 0.9020 0.9909
CR < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.0464 0.0187 < 0.001 0.0439 0.4978 0.0442
CC × CR 0.8826 0.9763 0.9440 0.9484 0.8880 0.8778 0.7653 0.7697 0.9344 0.8617 0.9841 0.8044
Treatment H + Al (mmol/L)
P (mg/L)
K (mg/L)
SOM (g/kg)
0–0.05 0.06–0.10 0.11–0.20 0–0.05 0.06–0.10 0.11–0.20 0–0.05 0.06–0.10 0.11–0.20 0–0.05 0.06–0.10 0.11–0.20
CC M + C 31.33 a 30.83 a 29.00 a 20.15 a 25.62 a 29.68 a 127.50 a 94.75 a 88.17 a 36.72 a 30.14 a 28.30 a
M + P 31.25 a 30.92 a 28.33 a 30.54 a 26.46 a 25.93 a 118.17 a 87.83 a 73.25 a 36.56 a 30.83 a 28.06 a
M + P + U 29.50 a 30.75 a 28.75 a 23.75 a 30.36 a 27.36 a 114.67 a 83.58 a 73.42 a 37.36 a 30.53 a 28.68 a
Fallow 38.42 a 30.25 a 28.58 a 28.59 a 30.27 a 36.26 a 120.42 a 85.67 a 83.17 a 35.32 a 30.83 a 27.83 a
CR 2016 41.04 a 36.00 a 33.29 a 26.70 a 24.60 a 47.61 a 104.08 b 76.67 b 64.79 b 35.93 a 31.08 a 27.29 a
2017 19.21 b 25.38 b 24.04 b 24.82 a 31.76 a 12.01 b 136.29 a 99.25 a 94.21 a 37.05 a 30.08 a 29.14 a
ANOVA CC 0.5206 0.9741 0.9707 0.1974 0.7736 0.4464 0.9692 0.8592 0.5735 0.5129 0.9127 0.9278
CR < 0.001 < 0.001 < 0.001 0.6116 0.0879 < 0.001 0.0460 0.0247 0.0024 0.2552 0.2043 0.0546
CC × CR 0.3400 0.9578 0.9277 0.1564 0.6906 0.8636 0.9581 0.5255 0.9099 0.6703 0.6379 0.7942
Treatment Cu (mg/L)
Fe (mg/L) Mn (mg/L) Zn (mg/L)
0–0.05 0.06–0.10 0.11–0.20 0–0.05 0.06–0.10 0.11–0.20 0–0.05 0.06–0.10 0.11–0.20 0–0.05 0.06–0.10 0.11–0.20
CC M + C 2.28 a 3.44 a 3.40 a 29.80 a 25.93 a 26.38 a 52.20 a 52.44 a 48.94 a 9.63 a 8.34 a 6.89 a
M + P 2.55 a 3.66 a 3.52 a 28.34 a 27.22 a 26.15 a 55.08 a 52.85 a 49.22 a 10.88 a 8.87 a 7.09 a
M + P + U 2.44 a 3.61 a 3.49 a 27.84 a 25.92 a 23.71 a 51.56 a 45.30 a 43.53 a 11.74 a 7.82 a 6.49 a
Fallow 2.52 a 3.29 a 3.22 a 29.48 a 26.00 a 24.09 a 51.25 a 48.17 a 46.79 a 11.26 a 9.88 a 7.54 a
CR 2016 2.72 a 4.64 a 4.66 a 6.87 b 9.65 b 9.15 b 63.16 a 70.43 a 62.03 a 13.08 a 12.54 a 9.19 a
2017 2.17 b 2.36 b 2.15 b 50.87 a 42.89 a 41.02 a 41.88 b 28.95 b 32.21 b 8.68 b 4.91 b 4.81 b
ANOVA CC 0.6257 0.1235 0.3198 0.8056 0.8074 0.1235 0.7912 0.3283 0.6723 0.5129 0.3036 0.6405
CR 0.0016 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 0.0001 < 0.001 < 0.001
CC × CR 0.3429 0.6396 0.9358 0.6278 0.9549 0.2149 0.2112 0.3219 0.8839 0.8468 0.4202 0.6017
M, Millet; C, Crotalaria; P, Pigeon pea (Cajanus cajans); U, Urochloa ruziziensis; CC, Cover crop; CR, Crop rotation; SOM, Soil organic matter;
ANOVA, Analysis of variance.
Means followed by the same letter in columns do not differ by the Turkey test for P < 0.05.
Adriano Stephan NASCENTE, et al. Cover Crops on Rotation Upland Rice and Soybean 345
Al, Cu, Mn and Zn contents were higher under one
cycle of cover crops than under two cycles. Al, P and
SOM contents had similar values in both growing
seasons (one or two cycles of cover crops).
Regarding the layer 0.11–0.20 m, pH, Ca, Mg, K
and Fe contents were higher under two cycles of cover
crops than under one cycle (Table 3). The contents of
Al, H + Al, P, Cu, Mn and Zn were higher under one
cycle of cover crops than under two cycles. SOM had
similar values in both growing seasons (one or two
cycles of cover crops).
There was no interaction between cover crops and
sample year for the soil physical properties evaluated
(Table 4). After two years (two cycles of cover crops),
the cover crops, including fallow, promoted improvement
in soil physical properties in the two layers studied.
Bulk density, microporosity and available water
capacity decreased, and total porosity, macroporosity,
S index (only in 0–0.10 m layer) and soil air capacity
increased.
In the 0–0.10 m layer, the cover crops, with the
exception of millet + crotalaria, provided improvements
in soil physical properties compared with fallow
(Table 4). They promoted reduction in bulk density
and increases in total porosity, macroporosity, S index
and soil air capacity. In this layer, the microporosity
and the available water capacity were not affected by
the cover crops. In the 0.11–0.20 m layer, all cover
crops promoted increases in macroporosity and soil air
capacity and a reduction in microporosity compared
with fallow. As the S index and soil air capacity were
highly related to soil pore arrangement, they presented
a positive correlation with macroporosity and total
porosity, and showed a negative correlation with bulk
density (Table 5).
There was no interaction between cover crops and
previous crop for yield components and grain yield of
upland rice and soybean (Table 6). The number of rice
pods per plant was higher under the cover crop millet +
crotalaria (187 panicles per plant) and differed from
fallow (145 panicles per plant). Number of grains per
panicle was higher in the cover crops millet + pigeon
pea (124 grains per panicle) and differed from fallow
(97 grains per panicle). There was no difference
presented by the cover crops for 1000-grain weight.
Grain yield was higher under millet + crotalaria (2 580
kg/hm2) and millet + pigeon pea (2 740 kg/hm
2), and
differed from fallow (1 981 kg/hm2).
Regarding growing season (one or two cycles of
cover crops), number of pods per plant was higher for
two cycles of cover crops (186) in 2016/2017 than one
cycle of cover crops (164) in 2015/2016. On the other
hand, number of grains per panicle was higher for one
cycle of cover crops (119) in 2015/2016 than for two
cycles of cover crops (99) in 2016/2017. Grain yield
and 1000-grain weight were similar in both growing
seasons (one and two cycles of cover crops).
There was no difference among number of pods per
plant, number of grains per panicle, 1000-grain weight
and grain yield of soybean under the cover crops
evaluated (Table 6). In the comparison of growing
Table 4. Soil physical characters as affected by cover crops, sampling times and soil layers.
Treatment BD (t/m3) TP Mip
Map
S index
SAC
AWC (mm)
L1 L2 L1 L2 L1 L2 L1 L2 L1 L2 L1 L2 L1 L2
CC M + C 1.40 ab 1.47 0.47 b 0.45 0.39 0.39 b 0.079 ab 0.056 a 0.023 ab 0.020 0.18 ab 0.14 a 7.50 7.41
M + P 1.39 b 1.46 0.48 a 0.45 0.40 0.40 b 0.082 a 0.056 a 0.024 ab 0.020 0.19 a 0.14 a 7.50 7.35
M + P + U 1.38 b 1.45 0.48 a 0.46 0.40 0.40 b 0.083 a 0.056 a 0.025 a 0.020 0.19 a 0.14 a 7.60 7.20
Fallow 1.42 a 1.47 0.47 b 0.45 0.40 0.41 a 0.064 b 0.040 b 0.021 b 0.019 0.15 b 0.10 b 7.40 7.45
CR 2016 1.43 a 1.49 a 0.47 b 0.44 b 0.41 a 0.40 a 0.060 b 0.039 b 0.021 b 0.019 a 0.14 b 0.10 b 7.81 a 7.85 a
2017 1.37 b 1.43 b 0.48 a 0.46 a 0.39 b 0.39 b 0.095 a 0.065 a 0.024 a 0.029 a 0.21 a 0.15 a 7.18 b 6.86 b
ANOVA CC 0.050 0.720 0.004 0.779 0.187 0.008 0.048 0.043 0.049 0.785 0.049 0.041 0.873 0.825
Y < 0.001 < 0.001 < 0.001 0.0001 < 0.001 0.024 < 0.001 < 0.001 0.001 0.4914 < 0.001 < 0.001 < 0.001 < 0.001
CC × Y 0.052 0.799 0.129 0.570 0.078 0.102 0.077 0.638 0.330 0.469 0.056 0.656 0.250 0.101
M, Millet; C, Crotalaria; P, Pigeon pea (Cajanus cajans); U, Urochloa ruziziensis; CC, Cover crop; CR, Crop rotation; BD, Bulk density; TP,
Total porosity; Mip, Microporosity; Map, Macroporosity; SAC, Soil air capacity; AWC, Available water capacity; L1, 0–0.10 cm; L2, 0.11–0.20 cm.
Means followed by the same letter in columns do not differ by Turkey test for P < 0.05.
Table 5. Correlation coefficient (r) among soil physical properties.
Trait BD TP Mip Map S SAC AWC
BD -0.99* 0.20 -0.89* -0.93* -0.85* -0.41
TP -0.92* -0.10 0.84* 0.90* 0.80* 0.40
Mip 0.06 0.15 -0.62* -0.46 -0.66* -0.32
Map -0.87* 0.83* -0.43 0.96* 0.99* 0.49
S -0.81* 0.79* -0.32 0.90* 0.92* 0.55
SAC -0.87* 0.81* -0.45 0.99* 0.88* 0.48
AWC 0.21 -0.08 0.11 -0.13 -0.16 -0.12
BD, Bulk density; TP, Total porosity; Mip, Microporosity; Map,
Macroporosity; SAC, Soil air capacity; AWC, Available water capacity.
Values followed by an asterisk are significant at 1% probability.
Values in regular and in bold are data for 2015 and 2017, respectively.
346 Rice Science, Vol. 25, No. 6, 2018
seasons (one or two cycles of cover crops), 1000-grain
weight and grain yield were higher in 2016/2017 (two
cycles of cover crops) than in 2015/2016 (one cycle of
cover crops). On the other hand, number of pods per
plant and number of grains per panicle were similar in
both growing seasons (one and two cycles of cover
crops).
DISCUSSION
The different mix of cover crops was unable to
provide different results in the chemical attributes of
the soil. Moreti et al (2007) reported that cover crops
could significantly affect the soil chemical attributes.
However, in our trial, these effects were similar
among the mixtures used in all the layers evaluated
(0–0.05, 0.06–0.10 and 0.11–0.20 m). On the other
hand, the system cover crops / cash crops / cover
crops / cash crops was more efficient to change soil
chemical properties than the system cover crops / cash
crops. This could be because two cycles of cover
crops produced more biomass. Pacheco et al (2011)
and Nascente et al (2013a) reported that cover crops
can produce high biomass, and during the period of
straw degradation, after chemical desiccation (herbicide
application), they can release nutrients to the soil. In
this sense, two cycles of cover crops reduced pH, Al
and H + Al contents and increased Ca, Mg, K and Fe
contents. According to Pacheco et al (2011), cover
crops can significantly change the soil chemical attributes.
Crusciol et al (2015) added that cover crops have great
potential for the absorption and accumulation of K+,
which is returned to the ground after their desiccation.
However, there is no increase in the SOM in the crop
rotations used. The use of cover crops in no-tillage
systems, due to keeping straw on the soil surface
without plowing, normally provides for increases in
the soil’s organic matter through the years (Nascente
et al, 2013a; Crusciol et al, 2015). However, only two
growing seasons using cover crops was not able to
significantly improve SOM when compared with one
season using cover crops. Nascente et al (2013b, 2014)
also reported similar values in the levels of SOM
when different cover crops were used in the no-tillage
system. The magnitude of SOM increase after using a
NTS is dependent on soil type, species and biomass
input of cover crops and regional climate (Santos et al,
2011). Short-term changes in total SOM due to the
soil management practices are often small and
difficult to assess (Zotarelli et al, 2007).
The improvement in soil physical properties due to
cover crops, especially under millet + pigeon pea and
millet + pigeon pea + Urochloa, is due to the
beneficial influence of grasses on the structure and
stability of soil aggregates, as demonstrated by several
researchers (Tisdall and Oades, 1979; Silva and
Table 6. Yield and nutrition traits in rice and soybean.
Treatment NPP NGP TGW (g)
GY (kg/hm2)
N (g/kg)
P (g/kg)
Rice Soybean Rice Soybean Rice Soybean Rice Soybean Rice Soybean Rice Soybean
CC M + C 187 a 72 a 116 ab 2.55 a 25.22 a 15.68 a 2 580 a 3 440 a 15.5 a 55.86 ab 3.02 a 5.32 a
M + P 169 ab 78 a 124 a 2.57 a 25.08 a 15.68 a 2 740 a 3 310 a 16.3 a 56.83 a 2.98 a 5.44 a
M + P + U 199 a 76 a 100 b 2.52 a 26.50 a 15.91 a 2 362 ab 3 538 a 16.8 a 55.30 ab 3.20 a 5.41 a
Fallow 145 b 74 a 97 b 2.53 a 24.18 a 15.47 a 1 981 b 3 297 a 16.7 a 54.72 b 2.90 a 5.18 a
CR 2016 164 b 76 a 119 a 2.52 a 25.42 a 15.36 b 2 522 a 3 252 b 18.1 a 58.3 a 3.32 a 5.92 a
2017 186 a 75 a 99 b 2.56 a 25.08 a 16.01 a 2 301 a 3 541 a 14.6 b 53.1 b 2.74 b 4.75 b
ANOVA CC 0.0421 0.4695 0.0450 0.7881 0.3730 0.5353 0.0159 0.6599 0.5130 0.0173 0.3924 0.2932
Y 0.0218 0.5761 0.0201 0.2683 0.7119 0.0074 0.1767 0.0434 0.0002 <0.001 0.0003 <0.001
CC × Y 0.7667 0.6116 0.0613 0.4787 0.8953 0.3951 0.3795 0.1899 0.4917 0.1063 0.8534 0.3224
Treatment K (g/kg) Ca (g/kg) Mg (g/kg)
Cu (mg/kg)
Fe (mg/kg) Mn (mg/kg)
Zn (mg/kg)
Rice Soybean Rice Soybean Rice Soybean Rice Soybean Rice Soybean Rice Soybean Rice Soybean
CC M + C 2.46 a 12.20 a 0.34 a 2.45 a 1.36 a 2.62 b 4.9 a 11.1 bc 33 a 77 a 31 a 22 a 32 a 40 a
M + P 2.44 a 12.90 a 0.33 a 2.52 a 1.36 a 2.74 a 5.1 a 11.5 ab 39 a 84 a 39 a 23 a 33 a 40 a
M + P + U 2.50 a 12.80 a 0.34 a 2.49 a 1.41 a 2.75 a 5.0 a 12.0 a 34 a 81 a 34 a 23 a 34 a 40 a
Fallow 2.44 a 13.05 a 0.33 a 2.52 a 1.33 a 2.72 a 4.4 a 10.6 c 34 a 81 a 29 a 22 a 31 a 38 a
CR 2016 2.61 a 7.98 b 0.37 a 2.34 b 1.48 a 2.87 a 4.8 a 10.9 b 45 a 79 a 38 a 21 b 33 a 41 a
2017 2.29 b 17.49 a 0.29 b 2.65 a 1.25 b 2.53 b 4.9 a 11.7 a 25 b 82 a 28 b 23 a 32 a 38 b
ANOVA CC 0.9462 0.6634 0.8895 0.5922 0.7513 0.0332 0.5219 0.0327 0.7881 0.4918 0.4452 0.6383 0.4684 0.7127
Y 0.0017 < 0.001 < 0.001 < 0.001 0.0006 < 0.001 0.6535 0.0149 0.0003 0.4498 0.0415 0.0047 0.5356 0.0079
CC × Y 0.4140 0.0955 0.7600 0.1132 0.7021 0.5705 0.7540 0.0599 0.7329 0.7714 0.3090 0.5321 0.0512 0.7450
M, Millet; C, Crotalaria; P, Pigeon pea (Cajanus cajans); U, Urochloa ruziziensis; CC, Cover crop; CR, Crop rotation; NPP, Number of panicles
per plant; NGP, Number of grains per panicle; TGW, 1000-grain weight; GY, Grain yield.
Means followed by the same letter in columns do not differ by Turkey test for P < 0.05.
Adriano Stephan NASCENTE, et al. Cover Crops on Rotation Upland Rice and Soybean 347
Mielniczuk, 1997; Rilling et al, 2002), and is
attributed to the high root density, which promotes the
aggregation of the particles by the constant soil water
uptake, periodic renewal of the root system and the
uniform distribution of soil exudates, which stimulate
microbial activity, whose byproducts act in the
formation and stabilization of aggregates (Silva and
Mielniczuk, 1997). Corroborating this information,
Silva et al (1998) and Nascente et al (2013b) found
that Urochloa ruziziensis improves soil aggregation.
In turn, Campos et al (1999) and Wohlenberg et al
(2004) verified that the sequence of crops with the
succession of grasses with legumes is the one that
favors the greater soil aggregation. The former authors
attributes this performance to the root system of the
grass and to the rate of legume decomposition,
creating favorable environment for the aggregation by
the roots action, soil cover, supply of organic material
and conservation of moisture favorable to the action of
the microorganisms.
In general, soil physical conditions favorable to plant
growth have been associated with a minimum air
porosity of 0.10 m3/m
3 (Dexter, 1988; Xu et al, 1992),
below which the diffusion of oxygen becomes limiting
to the functioning of the roots. In the two layers, all
values of macroporosity were lower than the limit of
0.10 m3/m
3, signaling some degree of compaction. The
highest values of macroporosity, in absolute values,
were verified in the soil where pigeon pea was included
as cover crop. Andrade et al (2009) found that pigeon
pea contributes to increased macroporosity in surface
layer of a soil grown with common bean.
Considering S of 0.035 as a limit between good
structural soil and soil with a tendency to become
degraded and S no more than 0.020 as indicative of
totally physically degraded soils (Dexter, 2004), it is
verified that only in the 0–0.10 m layer, the cover crops
provided values greater than 0.020. Andrade et al (2009)
verified that corn intercropped with Urochloa,
crotalaria and pigeon pea increases the S index in the
0–0.10 m layer of a soil cultivated with common bean.
In addition, in the two layers, all values of soil air
capacity were below 0.34, which is considered the
value that reflects good soil physical quality (Reynolds
et al, 2002). The decrease in the available water
capacity in the two soil layers, after two years (Table 4),
probably occurred due to changes in bulk density and
microporosity, although it did not correlate significantly
with these soil physical properties (Table 5). The
available water capacity depends on PWP and FC.
According to Reynolds et al (2002), the soil water
content in PWP is determined primarily by its clay
content, which is not greatly affected by soil management.
FC, in turn, is defined by a complex interaction of clay
content, bulk density and soil organic matter, and
changes in these factors are often compensated, albeit
partially, in their impact on the value of FC, being
responsible for the inconsistency of results.
Upland rice had the lowest grain yield under fallow,
which produced the lowest biomass. The biomass of
cover plants has significant influence on soil structure
and water and air flows (Cunha et al, 2011). The soil
under fallow showed higher soil bulk density and lower
total porosity, macroporosity and soil air capacity.
According to Guimarães and Moreira (2001), upland
rice development is decreased with increasing soil bulk
density. Guimarães et al (2011) added that increasing
soil bulk density can reduce root development with
significant effect on grain yield.
Regarding soybean yield, it was observed that the
mixture of cover crops did not affect its grain yield. In
the same way, Nascente and Crusciol (2012) reported
that species of cover crops (millet, Panicum maximum,
Urochloa ruziziensis, Urochloa brizantha and fallow)
do not affect soybean yield. Ricce et al (2011) added
that cover crops when correctly managed do not impair
soybean emergence and development, even with large
biomass. Besides, two cycles of cover crops provided
better development of soybean plants and allowed
increases in grain yield.
Our results showed that using cover crops at
offseason in agricultural systems that involves soybean
and upland rice at summer season in rotation for two
growing seasons was interesting once it improved soil
fertility, such as increasing Ca, Mg, K and Fe contents
in the soil and reducing pH, Al and H + Al contents,
reduced soil bulk density, improved total porosity of
soil and increased soybean grain yield. Besides, to be
environmental friendly, the use of cover crops allows
reducing soil erosion and it is better than fallow,
because using continuous fallowing in the NTS in
rotation with cash crops increases the number of weeds
in agricultural areas (Castro et al, 2011; Nascente et al,
2013a).
CONCLUSIONS
Cover crops alone provided no changes in soil
chemical properties. However, the rotation cover
crops / cash crops / cover crops / cash crops reduced
348 Rice Science, Vol. 25, No. 6, 2018
pH, Al and H + Al and increased Ca, Mg, K and Fe
contents in the soil. The cover crops millet + pigeon
pea and millet + pigeon pea + Urochloa improved soil
physical properties in relation to fallow, especially in
the 0–0.10 m soil layer. In spite of the improvement of
the soil physical properties after two years of rotation
with cover crops and cash crops, the soil physical
quality is still below the recommended level, according
to the values of macroporosity, S index and soil
aeration capacity. Upland rice production was higher
under mixtures of cover crops than under fallow,
mainly because of soil physical changes affected by
these mixtures of cover crops. Soybean grain yield
was similar for all cover crops tested, but was higher
after the rotation cover crops / upland rice / cover
crops than after only one cycle of cover crops.
ACKNOWLEDGEMENT
The authors are thankful to the National Council for
Scientific and Technological Development (CNPq)
and Foundation for Research Support of the State of
Goiás for their support.
SUPPLEMENTAL DATA
The following material is available in the online version of
this article at http://www.sciencedirect.com/science/
journal/16726308; http://www.ricescience.org.
Supplemental Fig. 1. Temperature and the amount of
rainfall data during the period of this study.
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